Solver Independent Rotating Workforce Scheduling

Musliu, Nysret; Schutt, Andreas; Stuckey, Peter J.

doi:10.1007/978-3-319-93031-2_31

Cited by 11 publications

(32 citation statements)

References 23 publications

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“…A new constraint model using a formulation in MiniZinc was introduced by [17] and evaluated using the lazy clause generation solver Chuffed and the MIP solver Gurobi. [8] extends the direct model in several ways, providing additional constraints to improve handling of infeasible instances and investigating complex real-world constraints and optimization goals.…”

Section: Rotating Workforce Schedulingmentioning

confidence: 99%

“…For initial evaluation we took all 2000 instances from a standard benchmark set 2 . These instances include 20 real life instances and other randomly generated instances [14,15,17]: The instances generated consist of 9 to 51 employees, 2 to 3 shift types, 3 to 4 minimal and 5 to 7 maximal length of work blocks, 1 to 2 minimal and 2 to 4 maximal length of days-off blocks, and minimal and maximal length of periods of consecutive shifts (D: 2 to 3 and 5 to 7, A: 2 to 3 and 4 to 6, N : 2 to 3 and 4 to 5). The same forbidden sequences as for real-life examples are used.…”

Section: Instancesmentioning

confidence: 99%

“…For the evaluation of an exact approach to RWS we use two different constraint models implemented in the MiniZinc modelling language as presented in [8], based on [17]. This section will give a short summary of the used models, for details refer to the paper.…”

Section: Constraint Modelsmentioning

confidence: 99%

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Instance space analysis for a personnel scheduling problem

Kletzander

Musliu

Smith‐Miles

2020

Ann Math Artif Intell

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This paper considers the Rotating Workforce Scheduling Problem, and shows how the strengths and weaknesses of various solution methods can be understood by the in-depth evaluation offered by a recently developed methodology known as Instance Space Analysis. We first present a set of features aiming to describe hardness of test instances. We create a new, more diverse set of instances based on an initial instance space analysis that reveals gaps in the instance space, and offers the opportunity to generate additional instances to add diversity to the test suite. The results of three algorithms on our extended instance set reveal insights based on this visual methodology. We observe different regions of strength and weakness in the instance space for each algorithm, as well as a phase transition from feasible to infeasible instances with more challenging instances at the phase transition boundary. This rigorous and insightful approach to analyzing algorithm performance highlights the critical role played by the choice of test instances, and the importance of ensuring diversity and unbiasedness of test instances to support valid conclusions.

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Section: Rotating Workforce Schedulingmentioning

confidence: 99%

Section: Instancesmentioning

confidence: 99%

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Instance space analysis for a personnel scheduling problem

Kletzander

Musliu

Smith‐Miles

2020

Ann Math Artif Intell

Self Cite

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“…In addition, a set of benchmark problems is presented that is inspired by problems from practice to evaluate computational methods for the RWS. Recently, the benchmark set has been further extended (Musliu et al 2018).…”

Section: Introductionmentioning

confidence: 99%

A decomposition heuristic for rotational workforce scheduling

Becker

2020

J Sched

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In rotational workforce planning, a schedule is constructed from a sequence of work and rest periods. Each employee starts at a different part of the schedule, and after a certain amount of time, the schedule repeats. The length of the schedule increases with a higher number of employees. At the same time, various constraints on work sequences and days off have to be considered. For a large number of employees, it is difficult to construct a schedule that meets the requirements. It is important to ensure low solution times independently of the problem instance characteristics. In this work, a novel decomposition approach for rotational shift scheduling is proposed. The decomposition exploits the fact that most constraints in rotational workforce scheduling are imposed on the work shift sequence. By considering a fixed set of blocks to cover the demand, the problem complexity can be greatly reduced. Given a fixed set of blocks, we propose a network model that determines whether a feasible sequence of shift blocks exists. The decomposition approach is applied to the problem structure of the Rotating Workforce Scheduling Problem but may be extended to different problem structures. In a computational study, the decomposition approach is compared to a mathematical formulation and previous exact and heuristic approaches. Computational results show that the decomposition approach greatly outperforms previous heuristics on the standard benchmarks.

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“…These problems are relevant in a broad context, of which many consider rotation aspects, too. In nurse rostering (Chiaramonte 2008;Azizi, Zolfaghari, and Liang 2010) and workforce scheduling (Ernst et al 2004;Musliu, Schutt, and Stuckey 2018), rotation is relevant to avoid boredom and fatigue or to cover a constrained shift system. In aircraft rotation (Clarke et al 1996) or machine scheduling (Ma, Chu, and Zuo 2010), rotation mechanisms allow to keep maintenance schedules or optimize usage patterns of machinery.…”

Section: Introductionmentioning

confidence: 99%

Rotational Diversity in Multi-Cycle Assignment Problems

Spieker

Gotlieb

Mossige

2019

AAAI

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In multi-cycle assignment problems with rotational diversity, a set of tasks has to be repeatedly assigned to a set of agents. Over multiple cycles, the goal is to achieve a high diversity of assignments from tasks to agents. At the same time, the assignments' profit has to be maximized in each cycle. Due to changing availability of tasks and agents, planning ahead is infeasible and each cycle is an independent assignment problem but influenced by previous choices. We approach the multi-cycle assignment problem as a two-part problem: Profit maximization and rotation are combined into one objective value, and then solved as a General Assignment Problem. Rotational diversity is maintained with a single execution of the costly assignment model. Our simple, yet effective method is applicable to different domains and applications. Experiments show the applicability on a multi-cycle variant of the multiple knapsack problem and a real-world case study on the test case selection and assignment problem, an example from the software engineering domain, where test cases have to be distributed over compatible test machines.

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Solver Independent Rotating Workforce Scheduling

Cited by 11 publications

References 23 publications

Instance space analysis for a personnel scheduling problem

Instance space analysis for a personnel scheduling problem

A decomposition heuristic for rotational workforce scheduling

Rotational Diversity in Multi-Cycle Assignment Problems

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